A new second-order method for blind signal separation from dynamic mixtures

This paper presents a new approach to separate colored stationary signals mixed by convolutive channels. A cost function is proposed by employing linear constraint to the demixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

A new second order method for blind signal separation from convolutive mixtures

This paper presents a new approach to separate colored signals mixed by FIR (finite impulse response) and MIMO (multiple-input multiple-output) channels. A cost function is proposed by employing linear constrainit to the de mixing vectors. The linear constraint is shown to be sufficient for avoiding trivial solution. The minimization of the cost function is performed using the Lagrangian method. Simulation results demonstrate the performance of the algorithm.

Adaptive blind source separation using constant modulus criterion and signal mutual information

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. It is known that the constant modulus (CM) criterion can be used to extract unknown source signals. However, the existing CM based algorithms normally extract the source signals in a serial manner. Consequently, the accuracy in extracting each source signal, except for the first one, depends on the accuracy of previous source extraction. This estimation error propagation (accumulation) causes severe performance degradation. In this paper, we propose a new adaptive separation algorithm that can separate all source signals simultaneously by directly updating the separation matrix. The superior performance of the new algorithm is demonstrated by simulation examples

Adaptive blind channel equalization based on constellation information of MPSK signal

In this paper, we propose a new adaptive algorithm for the blind equalization of an FIR (finite impulse response) channel excited by an M-ary phase shift keying (MPSK) signal. Different from the conventional constant modulus algorithm (CMA), which exploits the amplitude information of the input signal, the proposed algorithm exploits the full constellation information of the input signal. Theoretical analysis shows that the new algorithm has less mean square error (MSE), namely better equalization performance, in steady state than the CMA. Numerical simulations show the effectiveness of the new algorithm

A new blind signal separation algorithm for instantaneous MIMO system

We address the problem of adaptive blind source separation (BSS) from instantaneous multi-input multi-output (MIMO) channels. In this paper, we propose a new constant modulus (CM)-based algorithm which employ nonlinear function as the de-correlation term. Moreover, it is shown by theoretical analysis that the proposed algorithm has less mean square error (MSE), i.e., better separation performance, in steady state than the cross-correlation and constant modulus algorithm (CC-CMA). Numerical simulations show the effectiveness of the proposed result.

Comments on "A blind signal separation method for multiuser communications"

This correspondence first shows that the global convergence analysis of the method proposed in the above paper is incomplete. Then we provide a counter example to show that the sufficient condition for global convergence is incorrect.

A new blind-equalization algorithm for an FIR SIMO system driven by MPSK signal

We consider the problem of blind equalization of a finite impulse response and single-input multiple-output system driven by an M-ary phase-shift-keying signal. The existing single-mode algorithms for this problem include the constant modulus algorithm (CMA) and the multimodulus algorithm (MMA). It has been shown that the MMA outperforms the CMA when the input signal has no more than four constellation points, i.e., Mles4. In this brief, we present a new adaptive equalization algorithm that jointly exploits the amplitude and phase information of the input signal. Theoretical analysis shows that the proposed algorithm has less mean square error, i.e., better equalization performance, at steady state than the CMA regardless of the value of M. The superior performance of our algorithm to the CMA and the MMA is validated by simulation examples

A signal processing approach for elastic wave-based structural health monitoring using active piezoelectrics

A series of digital frequency filters (DFFs) were designed to screen diverse noises and the spectrographic analysis was conducted to isolate complex boundary reflection, which obscures the damage-induced signals. The scale-averaged wavelet power (SAP) technique was applied to enhance
the measurement accuracy of Time of Flight (TOF). As an example, the propagation characteristics of elastic wave in a structural beam of square cross-section were analyzed using such an approach and verified experimentally and numerically, with the consideration of the complicated wave scatter caused by the non-ignorable section dimensions.

Improved skeletal muscle oxidative enzyme activity and restoration of PGC-1α and PPARß/δ gene expression upon rosiglitazone treatment in obese patients with type 2 diabetes mellitus

Objective: To examine whether rosiglitazone alters gene expression of some key genes involved in mitochondrial biogenesis and oxidative capacity in skeletal muscle of type 2 diabetic patients, and whether this is associated with alterations in skeletal muscle oxidative capacity and lipid content.

Design: Skeletal muscle gene expression, mitochondrial protein content, oxidative capacity and lipid accumulation were measured in muscle biopsies obtained from diabetic patients, before and after 8 weeks of rosiglitazone treatment, and matched controls. Furthermore, whole-body insulin sensitivity and substrate utilization were assessed.

Subjects: Ten obese type 2 diabetic patients and 10 obese normoglycemic controls matched for age and BMI.

Methods: Gene expression and mitochondrial protein content of complexes I–V of the respiratory chain were measured by quantitative polymerase chain reaction and Western blotting, respectively. Histochemical staining was used to quantify lipid accumulation and complex II succinate dehydrogenase (SDH) activity. Insulin sensitivity and substrate utilization were measured during a hyperinsulinemic–euglycemic clamp with indirect calorimetry.

Results: Skeletal-muscle mRNA of PGC-1a and PPARb/d – but not of other genes involved in glucose, fat and oxidative metabolism – was significantly lower in diabetic patients (Po0.01). Rosiglitazone significantly increased PGC-1a (B2.2-fold, Po0.01) and PPARb/d (B2.6-fold, Po0.01), in parallel with an increase in insulin sensitivity, SDH activity and metabolic flexibility (Po0.01). Surprisingly, none of the measured mitochondrial proteins was reduced in type 2 diabetic patients, nor affected by rosiglitazone treatment. No alterations were seen in muscular fat accumulation upon treatment.

Conclusion: These results suggest that the insulin-sensitizing effect of rosiglitazone may involve an effect on muscular oxidative capacity, via PGC-1a and PPARb/d, independent of mitochondrial protein content and/or changes in intramyocellular lipid.

Reduced Skeletal Muscle Uncoupling Protein-3 Content in Prediabetic Subjects and Type 2 Diabetic Patients: Restoration by Rosiglitazone Treatment

Context: The mitochondrial uncoupling protein-3 (UCP3) has been implicated in the protection of the mitochondrial matrix against lipid-induced mitochondrial damage. Recent evidence points toward mitochondrial aberrations as a major contributor to the development of insulin resistance and diabetes, and UCP3 is reduced in diabetes.
Objective: We compared skeletal muscle UCP3 protein levels in prediabetic subjects [i.e. impaired glucose tolerance (IGT)], diabetic patients, and healthy controls and examined whether rosiglitazone treatment was able to restore UCP3.
Patients, Design, Intervention: Ten middle-aged obese men with type 2 diabetes mellitus [age, 61.4 ± 3.1 yr; body mass index (BMI), 29.8 ± 2.9 kg/m2], nine IGT subjects (age, 59.0 ± 6.6 yr; BMI, 29.7 ± 3.0 kg/m2), and 10 age- and BMI-matched healthy controls (age, 57.3 ± 7.4 yr; BMI, 30.1 ± 3.9 kg/m2) participated in this study. After baseline comparisons, diabetic patients received rosiglitazone (2 x 4 mg/d) for 8 wk.
Main Outcome Measures: Muscle biopsies were sampled to determine UCP3 and mitochondrial protein (complex I–V) content.
Results: UCP3 protein content was significantly lower in prediabetic IGT subjects and in diabetic patients compared with healthy controls (39.0 ± 28.5, 47.2 ± 24.7, and 72.0 ± 23.7 arbitrary units, respectively; P < 0.05), whereas the levels of the mitochondrial protein complex I–V were similar between groups. Rosiglitazone treatment for 8 wk significantly increased insulin sensitivity and muscle UCP3 content (from 53.2 ± 29.9 to 66.3 ± 30.9 arbitrary units; P < 0.05).
Conclusion: We show that UCP3 protein content is reduced in prediabetic subjects and type 2 diabetic patients. Eight weeks of rosiglitazone treatment restores skeletal muscle UCP3 protein in diabetic patients.

The effects of time pressure and experience on nurses' risk assessment decisions : a signal detection analysis

Background: Time pressure and, occasionally, suboptimal assessment decisions are features of nursing in acute care.

Objectives: To explore the effect of generic and specialist clinical experience on the ability to detect the need to take action in acute care and the impact of time pressure on nurses' decision-making performance.

Methods: Experienced acute care registered nurses (n = 241) were presented with 50 vignettes of real clinical risk assessments. Each vignette contained seven information cues. In response to these vignettes, nurses had to decide whether to intervene or not. The 26 vignettes were time limited and mixed randomly into the 50 cases. Signal detection analysis was used to establish nurses' performance, personal decision thresholds ([beta]), and their abilities (d') to distinguish a signal of clinical risk from the clinical noise of noncontributory information.

Results: Nurses had significantly lower d' and were significantly less likely to indicate intervening under time pressure. For ability-but not threshold-there was a significant interaction of time pressure and years of experience in acute care. With no time pressure, d' increased in line with years of experience. Under time pressure, there was no effect.

Discussion: Time pressure reduced nurses' ability to detect the need and the tendency to report intervening. Thus, there were more failures to report appropriate intervention under time pressure, and the positive effects of clinical experience were negated under time pressure. More and larger scale research on the effect on clinical outcomes of time pressured nursing choices is required.

Position estimation and tracking of an autonomous mobile sensor using received signal strength

In this paper, an algorithm for approximating the path of a moving autonomous mobile sensor with an unknown position location using Received Signal Strength (RSS) measurements is proposed. Using a Least Squares (LS) estimation method as an input, a Maximum-Likelihood (ML) approach is used to determine the location of the unknown mobile sensor. For the mobile sensor case, as the sensor changes position the characteristics of the RSS measurements also change; therefore the proposed method adapts the RSS measurement model by dynamically changing the pass loss value alpha to aid in position estimation. Secondly, a Recursive Least-Squares (RLS) algorithm is used to estimate the path of a moving mobile sensor using the Maximum-Likelihood position estimation as an input. The performance of the proposed algorithm is evaluated via simulation and it is shown that this method can accurately determine the position of the mobile sensor, and can efficiently track the position of the mobile sensor during motion.

Song as an honest signal of developmental stress in the zebra finch (Taeniopygia guttata)

In a wide range of bird species, females have been shown to express active preferences for males that sing more complex songs. Current sexual selection theory predicts that for this signal to remain an honest indicator of male quality, it must be associated with an underlying cost of development or maintenance. There has been considerable debate questioning the costs associated with song production and learning. Recently, the nutritional stress hypothesis proposed that song complexity could act as an indicator of early developmental history, since the song control nuclei in the brain are laid down early in life. Here we test the nutritional stress hypothesis, by investigating the effects of dietary stress on the quality of adult song produced. In addition, we tested the effects of elevated corticosterone during development on song production to test its possible involvement in mediating the effects of developmental stress. The results demonstrate that both dietary restriction and elevated corticosterone levels significantly reduced nestling growth rates. In addition, we found that experimentally stressed birds developed songs with significantly shorter song motif duration and reduced complexity. These results provide novel experimental evidence that complex song repertoires may have evolved as honest signals of male quality, by indicating early developmental rearing conditions.